Over the last two decades, the approach to addressability—how advertisers and publishers find and match target audiences with relevant ads—relied heavily on third-party identifiers like cookies and device IDs. But this required audiences to be tracked online without consent, leading to privacy concerns and eventually regulatory changes.
With the demise of third-party identifiers, marketers must embrace new solutions that protect consumer data. First-party data represents the gold standard of all options available to marketers today, and retail media networks are positioned to capitalize—provided they invest in privacy-preserving data and technology solutions for seamless activation of their first-party data.
Marketers must consider the spectrum of privacy preferences and available identifiers to understand the blind spots and evaluate them against the available and relevant solutions. To better understand the consumer spectrum and blind spots in addressability, let’s look at some scenarios.
Scenario 1: Authenticated, consented and first-party data identified
These consumers are logged into a website and willing to share their data with the company, as well as third-party partners working on the brand’s behalf, in exchange for a personalized experience. Marketers can establish one-to-one communication with these individuals on owned-and-operated properties, but they cannot identify the same individuals on external channels.
For example, firstname.lastname@example.org is the address John uses to log in to ABC Company’s website. But John also uses email@example.com while browsing other sites across the web.
Blind spot: Missing 1:1 identity link. ABC Company is unable to link the identity of John Doe on its website to the identity of John Doe on the open internet, so it can’t communicate with John Doe directly on external channels.
Scenario 2: Anonymous first-party data identified
These consumers browse a website without authentication (logging in), so their identity and privacy preferences are unknown. For example, John Doe browses ABC Company’s website without logging in. The first-party cookie on ABC’s website will capture John’s site behavior but doesn’t deterministically know if this is John Doe.
Blind spot: Partial identity and missing connectivity to external partners. ABC Company is unable to deterministically identify John Doe, and the insights that are available via first-party cookies can only be understood within its owned-and-operated ecosystem. The partial identity cannot be transferred to third-party partners, as they cannot read the contents of a first-party cookie.
What can ABC Company do to manage the blind spots in these first two scenarios? Here are a few solutions.
Inferred universal IDs use probabilistic inferences to associate a consumer with all the sites they visit on a browser (e.g., device fingerprinting or first-party cookies). But there could be a regulatory risk to this solution.
On-device, cohort-based solutions aggregate user data and place individuals into groups according to common interests. An example of this is Google’s Topics API, which can group consumers into buckets (like “travel enthusiasts”) based on browsing data.
With seller-defined audiences, publishers can use their first-party data to group audiences—usually based on the IAB’s taxonomy—and package them for advertisers to use (e.g., “users who are interested in beauty or personal care”). The IAB’s taxonomy gives the audience data a consistency that enables advertisers to use it across publishers. This is a budding solution, and adoption across publishers and ad-tech partners has been slow.
Contextual targeting takes keywords and webpage content into consideration, instead of user behavior, when displaying ads. For example, when John Doe is reading a food-related blog post, he could be served up with ads related to that content.
Scenario 3: Authenticated, consented first-party data; cross-domain/cross-platform identified
These consumers are willing to share their data with trusted companies and third-party partners. They are authenticated, with a strong presence in the first-party identity graph and can be matched to external third-party ID solutions.
Marketers can find these consumers in external channels for one-to-one communication. For example, firstname.lastname@example.org uses this address consistently while browsing the web, so all of ABC Company’s ad-tech partners can recognize John Doe on external channels.
Blind Spot: Fully connected ID is available, but scalability is a challenge. Approximately 20% of the total addressable market is authenticated and matched across publishers and platforms. Marketers relying on this scenario alone will not be able to scale advertising effectively and performance will be a problem.
There are two notable solutions for this kind of blind spot.
With universal IDs, consumers consent for their login data, email address or phone number to be used to create an anonymous online identifier (e.g., The Trade Desk UID2.0, LiveRamp Ramp ID, ID5, etc.). Marketers must partner with multiple ID providers to get the most value as these high-fidelity audiences present a scalability challenge.
Data clean rooms can enrich customer data with second-party data collaboration and provide better scalability and customer journey optimization.
Time for a new approach
Addressability in a post-cookie world is possible; it just needs a new approach. Consumers deserve better privacy protection across the open web, and regulatory changes will continue to disrupt the addressability ecosystem.
While there is no silver bullet or one-size-fits-all approach, marketers need a portfolio of solutions to compete in this new privacy-forward world. The best thing you can do is experiment with both ID- and non-ID-based solutions so you are ready for the future.